prepare_data

Loads and preprocesses a built-in dataset for clustering analysis.
Depending on the dataset name provided, different cleaning steps are applied.

An interactive platform for clustering analysis and teaching based on the 'shiny' web application framework.
Supports multiple popular clustering algorithms including k-means, hierarchical clustering,
DBSCAN (Density-Based Spatial Clustering of Applications with Noise), PAM (Partitioning Around Medoids),
GMM (Gaussian Mixture Model), and spectral clustering. Users can upload datasets or use built-in ones,
visualize clustering results using dimensionality reduction methods such as Principal Component Analysis (PCA)
and t-distributed Stochastic Neighbor Embedding (t-SNE), evaluate clustering quality via silhouette plots,
and explore method-specific visualizations and guides. For details on implemented methods, see:
Reynolds (2009, ISBN:9781598296975) for GMM;
Luxburg (2007) <doi:10.1007/s11222-007-9033-z> for spectral clustering.

Yijin Zhou

clusterWebApp

Universal Clustering Analysis Platform

prepare_data function

<dl><dt>dataset</dt>
<dd>A string specifying the dataset name. Options are: "iris", "USArrests", "mtcars", "CO2", "swiss", "Moons".</dd></dl>

Arguments

Prepare Built-in Datasets for Clustering — prepare_data

<dl>

<dt>dataset</dt>
<dd>A string specifying the dataset name. Options are: "iris", "USArrests", "mtcars", "CO2", "swiss", "Moons".</dd>

</dl>

prepare_data: Prepare Built-in Datasets for Clustering

Description

Usage

Value

Arguments

Details

Examples